• Title/Summary/Keyword: Linear scale

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Analysis of the Methodology for Linear Programming Optimality Analysis using Metamodelling Techniques

  • Lee, Young-Hae;Jeong, Chan-Seok
    • Journal of the military operations research society of Korea
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    • v.25 no.2
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    • pp.1-14
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    • 1999
  • Metamodels using response surface methodology (RSM) are used for the optimality analysis of linear programming (LP). They have the form of a simple polynomial, and predict the optimal objective function value of an LP for various levels of the constraints. The metamodelling techniques for optimality analysis of LP can be applied to large-scale LP models. What is needed is some large-scale application of the techniques to verify how accurate they are. In this paper, we plan to use the large scale LP model, strategic transport optimal routing model (STORM). The developed metamodels of the large scale LP can provide some useful information.

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Multi-Time Scale Separations and Optimal Control Problems of Multi-Parameter Singular Perturbation Systems (여러 매개상수 특이접동계에서의 여러 시간스케일 분리와 최적제어 문제)

  • Kim, Sam-Soo;Hong, Jae-Keun;Kim, Soo-Joong
    • Journal of the Korean Institute of Telematics and Electronics
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    • v.24 no.1
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    • pp.20-27
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    • 1987
  • The hierarchical approach method is proposed to sperate each different time scale sub-systems from linear time invariant multi-parameter singular perturbation systems. By means of this proposal, the original multi-parameter singular perturbation systems is completely separated into independent subsystems with each different time scale. It is also investigated that the controllability of the system is invariant. And this paper applies singular perturbation methods to the minimum control effort problem for linear time invariant systems with constrained controls. Also near-optimum control theory, which is based on dividing the total time interval with the time scales respectively, is proposed. As a result, the time scale separation method is show to be particularly useful in a near optimum design which can be otained through a decentralized control structure.

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Block-decomposition of a Linear Discrete Large-scale systems Via the Matrix Sign Function (행렬부호 함수에 의한 선형 이산치 대단위 계토의 블럭-분해)

  • 천희영;박귀태;권성하;이창훈
    • The Transactions of the Korean Institute of Electrical Engineers
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    • v.35 no.11
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    • pp.511-518
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    • 1986
  • An algorithm for block-decomposition of a linear, time-invariant, discrete large-scale systems is presented, based upon the matrix sign function on Z-plane. The block-decomposition is performed by defining a reference circle, a circular stripe and projection operators. Simulation study shows that the presented algorithm is very useful for multivariable control system's analysis and design.

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ROTUSTNESS LMPEROVEMENT OF DIRECT DECENTRALIZSD MODEL REFERENCE ADAPTIVE CONTROL

  • Chun, Hee-Young;Park, Gwi-Tae;Park, Seung-Kyu;Seo, Sam-Jun
    • 제어로봇시스템학회:학술대회논문집
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    • 1989.10a
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    • pp.856-861
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    • 1989
  • The control of a class of large scale systems formed by an arbitrary linear interconnections of linear time-invariant subsystems with unknown parameters is investigated. An approach is developed for improving the robustness of such a large scale system. In doing so, the new parameter adaptation algorithm(PAA) is used and a sufficient condition of stability is discussed by using the sector theory.

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Decentralized Iterative Learning Control in Large Scale Linear Dynamic Systems (대규모 선형 시스템에서의 비집중 반복 학습제어)

  • ;Zeungnam Bien
    • The Transactions of the Korean Institute of Electrical Engineers
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    • v.39 no.10
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    • pp.1098-1107
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    • 1990
  • Decentralized iterative learning control methods are presented for a class of large scale interconnected linear dynamic systems, in which iterative learning controller in each subsystem operates on its local subsystem exclusively with no exchange of information between subsystems. Suffcient conditions for convergence of the algorithms are given and numerical examples are illustrated to show the validity of the algorithms. In particular, the algorithms are useful for the systems having large uncertainty of inter-connected terms.

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An Adaptive Dynamic Range Linear Stretching Method for Contrast Enhancement (영상 강조를 위한 Adaptive Dynamic Range Linear Stretching 기법)

  • Kim, Yong-Min;Choi, Jae-Wan;Kim, Yong-Il
    • Korean Journal of Remote Sensing
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    • v.26 no.4
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    • pp.395-401
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    • 2010
  • Image enhancement algorithm aims to improve the visual quality of low contrast image through eliminating the noise and blurring, increasing contrast, and raising detail. This paper proposes adaptive dynamic range linear stretching(ADRLS) algorithm based on advantages of existing methods. ADRLS method is focused on generating sub-histograms of the majority through partitioning the histogram of input image and applying adaptive scale factor. Generated sub-histograms are finally applied by linear stretching(LS) algorithm. In order to validate proposed method, it is compared with LS and histogram equalization(HE) algorithm generally used. As the result, the proposed method show to improve contrast of input image and to preserve distinct characteristics of histogram by controlling excessive change of brightness.

Efficient Linear Path Query Processing using Information Retrieval Techniques for Large-Scale Heterogeneous XML Documents (정보 검색 기술을 이용한 대규모 이질적인 XML 문서에 대한 효율적인 선형 경로 질의 처리)

  • 박영호;한욱신;황규영
    • Journal of KIISE:Databases
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    • v.31 no.5
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    • pp.540-552
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    • 2004
  • We propose XIR-Linear, a novel method for processing partial match queries on large-scale heterogeneous XML documents using information retrieval (IR) techniques. XPath queries are written in path expressions on a tree structure representing an XML document. An XPath query in its major form is a partial match query. The objective of XIR-Linear is to efficiently support this type of queries for large-scale documents of heterogeneous schemas. XIR-Linear has its basis on the schema-level methods using relational tables and drastically improves their efficiency and scalability using an inverted index technique. The method indexes the labels in label paths as key words in texts, and allows for finding the label paths that match the queries far more efficiently than string match used in conventional methods. We demonstrate the efficiency and scalability of XIR-Linear by comparing it with XRel and XParent using XML documents crawled from the Internet. The results show that XIR-Linear is more efficient than both XRel and XParent by several orders of magnitude for linear path expressions as the number of XML documents increases.

Cognitive Contrast Enhancement of Image Using Adaptive Parameter Based on Non-Linear Masking (비선형 마스킹 기법 기반의 적응적 파라미터를 이용한 영상의 인지적 대비 향상)

  • Kim, Kyoung-Su;Kim, Jong-Sung;Lee, Cheol-Hee
    • Journal of Korea Multimedia Society
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    • v.14 no.11
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    • pp.1365-1372
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    • 2011
  • This paper proposes a cognitive contrast enhancement algorithm based on the non-linear masking to advance low cognitive contrast in dark regions of images. In order to improve brightness in dark regions of an image, we propose a new contrast enhancement algorithm based on the non-linear masking using regional adaptive parameters of an image. For performance evaluation of the proposed method, chromaticity and saturation comparison as a quantitative assessment and z-score comparison as a qualitative assessment were executed between test images and their simulated images by SSR, MSR, a conventional non-linear masking and the proposed method, respectively. As a result, the proposed method showed low chromaticity and saturation difference and improved cognitive contrast for the three methods.